import os
import sys
import importlib
import json
import numpy as np
import pandas as pd
import scipy
import scipy.ndimage as snd
import skimage
import uuid
from matplotlib import pyplot as plt
import matplotlib as mpl
import cv2
import plotly
import plotly.express as px
import plotly.graph_objects as go


if os.getcwd().split("/")[-1] == "notebooks":  # if cwd is located where this file is
    os.chdir("../..")  # go two folders upward (the if statement prevents error if cell is rerun)
directory_path = os.path.abspath(os.path.join("src"))
if directory_path not in sys.path:
    sys.path.append(directory_path)
print(directory_path)
import src.EyeTraumaAnalysis

C:\Users\ethan\PycharmProjects\EyeTraumaAnalysis\src\notebooks\src
cwd:  C:\Users\ethan\PycharmProjects\EyeTraumaAnalysis\src\notebooks

Traceback (most recent call last):
  File "C:\Users\ethan\PycharmProjects\EyeTraumaAnalysis\src\EyeTraumaAnalysis\main.py", line 19, in <module>
    li_df = pd.read_excel(prepath+"data/01_raw/data_li.xlsx", dtype={"centerX":float, "centerY":float})
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\ethan\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\util\_decorators.py", line 211, in wrapper
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\ethan\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\util\_decorators.py", line 331, in wrapper
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\ethan\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\io\excel\_base.py", line 482, in read_excel
    io = ExcelFile(io, storage_options=storage_options, engine=engine)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\ethan\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\io\excel\_base.py", line 1652, in __init__
    ext = inspect_excel_format(
          ^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\ethan\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\io\excel\_base.py", line 1525, in inspect_excel_format
    with get_handle(
         ^^^^^^^^^^^
  File "C:\Users\ethan\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\io\common.py", line 865, in get_handle
    handle = open(handle, ioargs.mode)
             ^^^^^^^^^^^^^^^^^^^^^^^^^
FileNotFoundError: [Errno 2] No such file or directory: 'data/01_raw/data_li.xlsx'

importlib.reload(src.EyeTraumaAnalysis);

Load metrics

!pip3 install pickle5
import pickle5 as pickle

Requirement already satisfied: pickle5 in c:\users\ethan\pycharmprojects\eyetraumaanalysis\venv\lib\site-packages (0.0.12)

# reload data as pickle protocol 4
with open("../../data/03_first_25percent_metrics/color_and_spatial_metrics" + ".pkl", "rb") as fh:
  data = pickle.load(fh)
  data.to_pickle("../../data/03_first_25percent_metrics/color_and_spatial_metrics" + "_p4" + ".pkl")
with open("../../data/03_first_25percent_metrics/color_and_spatial_metrics_flat" + ".pkl", "rb") as fh:
  data = pickle.load(fh)
  data.to_pickle("../../data/03_first_25percent_metrics/color_and_spatial_metrics_flat" + "_p4" + ".pkl")
with open("../../data/03_first_25percent_metrics/color_and_spatial_metrics_agg" + ".pkl", "rb") as fh:
  data = pickle.load(fh)
  data.to_pickle("../../data/03_first_25percent_metrics/color_and_spatial_metrics_agg" + "_p4" + ".pkl")

all_metrics = pd.read_pickle("../../data/03_first_25percent_metrics/color_and_spatial_metrics" + ".pkl")
all_metrics_flat = pd.read_pickle("../../data/03_first_25percent_metrics/color_and_spatial_metrics_flat" + ".pkl")
all_metrics_agg = pd.read_pickle("../../data/03_first_25percent_metrics/color_and_spatial_metrics_agg" + ".pkl")
# all_metrics = pd.read_pickle("../../data/03_first_25percent_metrics/color_and_spatial_metrics" + "_p4" + ".pkl")
# all_metrics_flat = pd.read_pickle("../../data/03_first_25percent_metrics/color_and_spatial_metrics_flat" + "_p4" + ".pkl")
# all_metrics_agg = pd.read_pickle("../../data/03_first_25percent_metrics/color_and_spatial_metrics_agg" + "_p4" + ".pkl")

notebook_name = "4b_descriptive_subsets"

def get_path_to_save(
        plot_props:dict=None, file_prefix="",
        save_filename:str=None, save_in_subfolder:str=None, extension="jpg", dot=".", create_folder_if_necessary=True):
    replace_characters = {
        "$": "",
        "\\frac":"",
        "\\mathrm":"",
        "\\left(":"(",
        "\\right)":")",
        "\\left[":"[",
        "\\right]":"]",
        "\\": "",
        "/":"-",
        "{": "(",
        "}": ")",
        "<":"",
        ">":"",
        "?":"",
        "_":"",
        "^":"",
        "*":"",
        "!":"",
        ":":"-",
        "|":"-",
        ".":"_",
    }
    # define save_filename based on plot_props
    if save_filename is None:
        save_filename = "unnamed"

    save_path = ["outputs", notebook_name,]
    if save_in_subfolder is not None:
        if isinstance(save_in_subfolder, (list, tuple, set, np.ndarray) ):
            save_path.append(**save_in_subfolder)
        else:  # should be a string then
            save_path.append(save_in_subfolder)
    save_path = os.path.join(*save_path)

    if not os.path.exists(save_path) and create_folder_if_necessary:
        os.makedirs(save_path)
    return os.path.join(save_path, file_prefix+save_filename+dot+extension)

def save_plotly_figure(fig: plotly.graph_objs.Figure,
                       title: str,
                       animated=False,
                       scale=None,
                       save_in_subfolder:str=None,
                       extensions=None
                       ):
    if scale is None:
        scale = 4
    if extensions is None:
        extensions = ["html"]
        if not animated:
            # options = ['png', 'jpg', 'jpeg', 'webp', 'svg', 'pdf', 'eps', 'json']
            extensions += ["png","pdf"]
    extensions = ["html"] # override due to png saving error
    for extension in extensions:
        try:
            if extension in ["htm","html"]:
                #fig.update_layout(title=dict(visible=False))
                # fig.write_html( get_path_to_save(save_filename=title, save_in_subfolder=save_in_subfolder, extension=extension),
                #     full_html=True, include_plotlyjs="directory" )
                fig.write_html(f"C:/Users/ethan/PycharmProjects/EyeTraumaAnalysis/outputs/RSY_4/{title}.{extension}")
            else:
                #if extension == "png":
                #    fig.update_layout(title=dict(visible=False))
                fig.write_image(get_path_to_save(save_filename=title, save_in_subfolder=save_in_subfolder, extension=extension), scale=scale)
        except ValueError as exc:
            import traceback
            traceback.print_exception(exc)

# def save_plotly_figure(fig: plotly.graph_objs.Figure, title: str, directory="C:/Users/ethan/PycharmProjects/EyeTraumaAnalysis/outputs/kmeans-descriptive-subsets/"):
#     fig.write_image(os.path.join(directory, title + ".png"))
#     fig.write_html( os.path.join(directory, title + ".html"),
#                     full_html=True, include_plotlyjs="directory" )

color_discrete_map = {
    "True":           px.colors.qualitative.Plotly[2], # green
    "Maybe":          px.colors.qualitative.Plotly[0], # blue
    "False":          px.colors.qualitative.Plotly[1], # red
}
pattern_shape_map = {}
category_orders = {
    "Labels-Value": ["False", "Maybe", "True"],
    "facet_col": [False, True],
    "facet_row": [False, True],
}

# This is only the start. It will be added to programmatically later
var_labels = {
    "Labels-Value": "Conjunctiva cluster",
    "Values-Color-Center-H": "Center H",
    "Values-Color-Center-S": "Center S",
    "Values-Color-Center-V": "Center V",
    "Values-Color-Range-H": "Range H",
    "Values-Color-Range-S": "Range S",
    "Values-Color-Range-V": "Range V",
    "Values-Location-Mean-x": "Mean x",
    "Values-Location-Mean-y": "Mean y",
    "Values-Location-SD-x": "SD x",
    "Values-Location-SD-y": "SD y",
}

var_labels_copy = var_labels.copy()
suffixes = ["-H","-x"]
for var_label_key in var_labels_copy:
    for suffix in suffixes:
        if var_label_key.endswith(suffix):
            sep = suffix[:1]  # should be "-"
            suffix_letter = suffix[1:]  # should be "-H" or "-x"
            # Get name up to suffix letter e.g. "Values-Color-Center-"
            var_label_key_prefix = var_label_key[0:-len(suffix_letter)]
            # Get all possible suffixes for the prefix i.e. "H", "S", "V"
            suffix_letter_options = [var_label_key[len(var_label_key_prefix):] for var_label_key in var_labels_copy
                                          if var_label_key.startswith(var_label_key_prefix)]
            combined_suffix_letters = "".join(suffix_letter_options)
            # Get combined value
            var_label_val_prefix = var_labels[var_label_key_prefix + suffix_letter][:-len(suffix_letter)]
            combined_var_label_key = var_label_key_prefix + combined_suffix_letters
            combined_var_label_val = var_label_val_prefix + combined_suffix_letters
            var_labels[combined_var_label_key] = combined_var_label_val


# Add labels for ranks
var_labels_copy = var_labels.copy()
for var_label_key in var_labels_copy:
    if var_label_key.startswith("Values-"):
        var_label_key_suffix = var_label_key.split("Values-",maxsplit=1)[-1]
        var_labels[f"Ranks-{var_label_key_suffix}"] = var_labels[var_label_key] + " (Rank)"

# Add labels
for var_label_key in all_metrics_flat.columns:
    for comparator in [">","<"]:
        if comparator in var_label_key:
            stem, comparison = var_label_key.split(comparator, maxsplit=1)
            if stem in var_labels:
                var_labels[var_label_key] = \
                    (var_labels[stem] + comparator + comparison).replace(">=","≥").replace("<=","≤")
            else:
                print(var_label_key, stem)
                print(var_labels_copy)
                raise KeyError

#point_hover_data = ["Values-Color-Center-HSV","Ranks-Color-Center-HSV",
#                    "Values-Location-Mean-xy","Ranks-Location-Mean-xy",
#                    "Values-Location-SD-xy","Ranks-Location-SD-xy"]
point_hover_data = {
    "Values-Color-Center-H": False,
    "Values-Color-Center-S": False,
    "Values-Color-Center-V": False,
    "Ranks-Color-Center-H": False,
    "Ranks-Color-Center-S": False,
    "Ranks-Color-Center-V": False,
    "Values-Color-Center-HSV":True,
    "Ranks-Color-Center-HSV":True,
    "Values-Location-Mean-xy":True,
    "Ranks-Location-Mean-xy":True,
    "Values-Location-SD-xy":True,
    "Ranks-Location-SD-xy":True,
}
roc_hover_data = {
    "sensitivity":":0.2%",
    "1-specificity":":0.2%",
    "threshold":True
}

plotly_template = "plotly_dark"  #"simple_white"

Plot

fig = px.histogram(all_metrics_flat, x="Values-Color-Center-H", marginal="box", opacity=0.6,
                   barmode="group", histnorm="percent",
                   facet_col="Values-Color-Center-H>=100",
                   color="Labels-Value", color_discrete_map=color_discrete_map,
                    category_orders=category_orders, labels=var_labels, template=plotly_template)
fig.update_layout(bargap=0.04)
fig.update_layout(font=dict(family="Arial",size=16,), margin=dict(l=20, r=20, t=20, b=20))
fig.update_xaxes(matches=None)
fig.for_each_xaxis(lambda axis: axis.update(showticklabels=True))
fig.show()
title = "HSV histogram with box plot- H val split at GTE 100 - 3-24-2023"
save_plotly_figure(fig, title)

fig = px.histogram(all_metrics_flat, x="Ranks-Color-Center-H", marginal="box", opacity=0.6,
                   barmode="group",
                   facet_col="Values-Color-Center-V>=75",
                   color="Labels-Value", color_discrete_map=color_discrete_map,
                category_orders=category_orders, labels=var_labels, template=plotly_template)
fig.update_layout(bargap=0.04)
fig.update_layout(font=dict(family="Arial",size=16,), margin=dict(l=20, r=20, t=20, b=20))
fig.show()
title = "HSV histogram with box plot- H rank split at V val GT 75 - 3-24-2023"
save_plotly_figure(fig, title)

fig = px.histogram(all_metrics_flat, x="Ranks-Color-Center-H", marginal="box", opacity=0.6,
                   barmode="group",
                   facet_col="Ranks-Color-Center-V>=4",
                   color="Labels-Value", color_discrete_map=color_discrete_map,
                category_orders=category_orders, labels=var_labels, template=plotly_template)
fig.update_layout(bargap=0.04)
fig.update_layout(font=dict(family="Arial",size=16,), margin=dict(l=20, r=20, t=20, b=20))
fig.show()
title = "HSV histogram with box plot- H val split at V rank GTE 4 - 3-24-2023"
save_plotly_figure(fig, title)

fig = px.histogram(all_metrics_flat, x="Ranks-Color-Center-H", marginal="box", opacity=0.6,
                   barmode="group",
                   facet_col="Ranks-Color-Center-V>=5",
                   color="Labels-Value", color_discrete_map=color_discrete_map,
                category_orders=category_orders, labels=var_labels, template=plotly_template)
fig.update_layout(bargap=0.04)
fig.update_layout(font=dict(family="Arial",size=16,), margin=dict(l=20, r=20, t=20, b=20))
fig.show()
title = "HSV histogram with box plot- H val split at V rank GTE 5 - 3-24-2023"
save_plotly_figure(fig, title)

fig = px.histogram(all_metrics_flat, x="Ranks-Color-Center-H", marginal="box", opacity=0.6,
                   barmode="group",
                   facet_col="Ranks-Color-Center-V>=6",
                   color="Labels-Value", color_discrete_map=color_discrete_map,
                   category_orders=category_orders, labels=var_labels, template=plotly_template)
fig.update_layout(bargap=0.04)
fig.update_layout(font=dict(family="Arial",size=16,), margin=dict(l=20, r=20, t=20, b=20))
fig.show()
title = "HSV histogram with box plot- H val split at V rank GTE 6 - 3-24-2023"
save_plotly_figure(fig, title)

fig = px.histogram(all_metrics_flat, x="Ranks-Color-Center-H", marginal="box", opacity=0.6,
                   barmode="group",
                   facet_col="Values-Color-Center-V>=75",
                   facet_row="Values-Color-Center-S>=155",
                   color="Labels-Value", color_discrete_map=color_discrete_map,
                   category_orders=category_orders, labels=var_labels, template=plotly_template)
fig.update_layout(bargap=0.04)
fig.update_layout(font=dict(family="Arial",size=16,), margin=dict(l=20, r=20, t=20, b=20))
fig.show()
title = "HSV histogram- H val split at V GTE 75 and S GTE 75 - 3-24-2023"
save_plotly_figure(fig, title)